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Thematische Bibliographien / Respiratory pattern classification / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Respiratory pattern classification“

Autor: Grafiati

Veröffentlicht am 27. Juni 2021

Zuletzt aktualisiert am 29. Juli 2025

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1

Tasar, Beyda, Orhan Yaman, and Turker Tuncer. "Accurate respiratory sound classification model based on piccolo pattern." Applied Acoustics 188 (January 2022): 108589. http://dx.doi.org/10.1016/j.apacoust.2021.108589.

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Lee, Do-Kyeong, Jae-Sung Choi, Seong-Jun Choi, Min-Hyung Choi, and Min Hong. "Classification of Chronic Obstructive Pulmonary Disease (COPD) Through Respiratory Pattern Analysis." Diagnostics 15, no. 3 (2025): 313. https://doi.org/10.3390/diagnostics15030313.

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Background: This study proposes a classification system for predicting chronic obstructive pulmonary disease (COPD) patients and non-patients based on image and text data. Method: This study measured the respiratory volume based on thermal images, stored the respiratory data, and derived features related to respiratory patterns, including the total respiratory volume, average distance between expirations, average distance between inspirations, and total respiratory rate. The data for each feature were stored in text format. The four features saved as text were scaled using Z-score normalizatio

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Hong, Jin-Woo, Seong-Hoon Kim, and Gi-Tae Han. "Detection of Multiple Respiration Patterns Based on 1D SNN from Continuous Human Breathing Signals and the Range Classification Method for Each Respiration Pattern." Sensors 23, no. 11 (2023): 5275. http://dx.doi.org/10.3390/s23115275.

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Human respiratory information is being used as an important source of biometric information that can enable the analysis of health status in the healthcare domain. The analysis of the frequency or duration of a specific respiration pattern and the classification of respiration patterns in the corresponding section for a certain period of time are important for the utilization of respiratory information in various ways. Existing methods require window slide processing to classify sections for each respiration pattern from the breathing data for a certain time period. In this case, when multiple

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Kunczik, Janosch, Kerstin Hubbermann, Lucas Mösch, Andreas Follmann, Michael Czaplik, and Carina Barbosa Pereira. "Breathing Pattern Monitoring by Using Remote Sensors." Sensors 22, no. 22 (2022): 8854. http://dx.doi.org/10.3390/s22228854.

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The ability to continuously and unobtrusively monitor and classify breathing patterns can be very valuable for automated health assessments because respiration is tightly coupled to many physiological processes. Pathophysiological changes in these processes often manifest in altered breathing patterns and can thus be immediately detected. In order to develop a breathing pattern monitoring system, a study was conducted in which volunteer subjects were asked to breathe according to a predefined breathing protocol containing multiple breathing patterns while being recorded with color and thermal

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Park, Jinho, Thien Nguyen, Soongho Park, Brian Hill, Babak Shadgan, and Amir Gandjbakhche. "Two-Stream Convolutional Neural Networks for Breathing Pattern Classification: Real-Time Monitoring of Respiratory Disease Patients." Bioengineering 11, no. 7 (2024): 709. http://dx.doi.org/10.3390/bioengineering11070709.

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A two-stream convolutional neural network (TCNN) for breathing pattern classification has been devised for the continuous monitoring of patients with infectious respiratory diseases. The TCNN consists of a convolutional neural network (CNN)-based autoencoder and classifier. The encoder of the autoencoder generates deep compressed feature maps, which contain the most important information constituting data. These maps are concatenated with feature maps generated by the classifier to classify breathing patterns. The TCNN, single-stream CNN (SCNN), and state-of-the-art classification models were

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Speranskaya, A. A., O. P. Baranova, M. A. Vasilyeva, and I. V. Amosov. "RADIATION DIAGNOSIS OF RARE FORMS OF RESPIRATORY ORGAN SARCOIDOSIS." Journal of radiology and nuclear medicine 99, no. 4 (2018): 175–83. http://dx.doi.org/10.20862/0042-4676-2018-99-4-175-183.

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Objective: to evaluate the clinical and radiological features of rare forms of sarcoidosis of the respiratory organs (SRO).Material and methods. In 2006 to 2016, the Research Institute of Interstitial and Orphan Lung Diseases followed up 599 patients with sarcoidosis. 36 patients (6.0%) of them had atypical clinical and radiation manifestations that did not correspond to the traditional radiation pattern and the existing X-ray classification of SRO. Stages 2, 3, and 4 pulmonary sarcoidosis was diagnosed in 26, 7, and 3 patients, respectively. The patients’ mean age was 38.2±7.4 years (the fema

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Boulding, Richard, Rebecca Stacey, Rob Niven, and Stephen J. Fowler. "Dysfunctional breathing: a review of the literature and proposal for classification." European Respiratory Review 25, no. 141 (2016): 287–94. http://dx.doi.org/10.1183/16000617.0088-2015.

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Dysfunctional breathing is a term describing breathing disorders where chronic changes in breathing pattern result in dyspnoea and other symptoms in the absence or in excess of the magnitude of physiological respiratory or cardiac disease. We reviewed the literature and propose a classification system for the common dysfunctional breathing patterns described. The literature was searched using the terms: dysfunctional breathing, hyperventilation, Nijmegen questionnaire and thoraco-abdominal asynchrony. We have summarised the presentation, assessment and treatment of dysfunctional breathing, and

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Hao, Zhanjun, Yue Wang, Fenfang Li, Guozhen Ding, and Yifei Gao. "mmWave-RM: A Respiration Monitoring and Pattern Classification System Based on mmWave Radar." Sensors 24, no. 13 (2024): 4315. http://dx.doi.org/10.3390/s24134315.

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Breathing is one of the body’s most basic functions and abnormal breathing can indicate underlying cardiopulmonary problems. Monitoring respiratory abnormalities can help with early detection and reduce the risk of cardiopulmonary diseases. In this study, a 77 GHz frequency-modulated continuous wave (FMCW) millimetre-wave (mmWave) radar was used to detect different types of respiratory signals from the human body in a non-contact manner for respiratory monitoring (RM). To solve the problem of noise interference in the daily environment on the recognition of different breathing patterns, the sy

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Bahoura, Mohammed. "Pattern recognition methods applied to respiratory sounds classification into normal and wheeze classes." Computers in Biology and Medicine 39, no. 9 (2009): 824–43. http://dx.doi.org/10.1016/j.compbiomed.2009.06.011.

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Dokur, Zümray. "Respiratory sound classification by using an incremental supervised neural network." Pattern Analysis and Applications 12, no. 4 (2008): 309–19. http://dx.doi.org/10.1007/s10044-008-0125-y.

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Wijaya, David, and Anastasia Rita Widiarti. "Batik classification using KNN algorithm and GLCM features extraction." E3S Web of Conferences 475 (2024): 02012. http://dx.doi.org/10.1051/e3sconf/202447502012.

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Batik is one of the Indonesian cultures that has been recognized by UNESCO as an intellectual right of Indonesia. The popularity of batik internationally raises concerns about the Indonesian people’s understanding of batik if Indonesian people only refer to all types of batik just as ‘batik’. By utilizing K-Nearest Neighbour (KNN) algorithm which is a simple classification algorithm, then a system can be created that can classify batik types. The first step of KNN is training, which stores each training pattern. The second step is classification, whenever classifying a pattern, KNN examine all

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DOKUR, ZÜMRAY, and TAMER ÖLMEZ. "CLASSIFICATION OF RESPIRATORY SOUNDS BY USING AN ARTIFICIAL NEURAL NETWORK." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 04 (2003): 567–80. http://dx.doi.org/10.1142/s0218001403002526.

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In this paper, a classification method for respiratory sounds (RSs) in patients with asthma and in healthy subjects is presented. Wavelet transform is applied to a window containing 256 samples. Elements of the feature vectors are obtained from the wavelet coefficients. The best feature elements are selected by using dynamic programming. Grow and Learn (GAL) neural network, Kohonen network and multi-layer perceptron (MLP) are used for the classification. It is observed that RSs of patients (with asthma) and healthy subjects are successfully classified by the GAL network.

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Wang, Qisong, Zhening Dong, Dan Liu, et al. "Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature." Journal of Healthcare Engineering 2021 (August 9, 2021): 1–18. http://dx.doi.org/10.1155/2021/9376662.

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Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76–81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuo

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Pinto, Jorge, Hernando González, Carlos Arizmendi, Hernán González, Yecid Muñoz, and Beatriz F. Giraldo. "Analysis of the Cardiorespiratory Pattern of Patients Undergoing Weaning Using Artificial Intelligence." International Journal of Environmental Research and Public Health 20, no. 5 (2023): 4430. http://dx.doi.org/10.3390/ijerph20054430.

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The optimal extubating moment is still a challenge in clinical practice. Respiratory pattern variability analysis in patients assisted through mechanical ventilation to identify this optimal moment could contribute to this process. This work proposes the analysis of this variability using several time series obtained from the respiratory flow and electrocardiogram signals, applying techniques based on artificial intelligence. 154 patients undergoing the extubating process were classified in three groups: successful group, patients who failed during weaning process, and patients who after extub

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Ngo, Thi Viet Trinh, Dao Dinh, and Hai Anh Ha. "Analysis of disease pattern and drug formulary at Da Nang Hospital for Lung Diseases before the time of the COVID-19 pandemic." DTU Journal of Science & Technology 5, no. 54 (2022): 172–79. https://doi.org/10.5281/zenodo.8346579.

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Introduction: Since the COVID-19 outbreak, there have been studies showing the impact of the disease on other respiratory diseases, leading to an impact on prevention and treatment. Therefore, it is necessary to analyze data on disease patterns and hospital drug lists in order to have data as a basis for adjustment for the periods during and after the epidemic, and to meet the treatment needs that may change. Methods: In this study, we collected information from the drug supply, treatment activities, drug used and value. Drug categories and ABC analysis were used for drug formulary. ICD-10 (In

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Gradova, Yulia V., and Sergey P. Kovalev. "COVID-19 in dogs: classification of course and its radiological characteristics." Veterinariya, Zootekhniya i Biotekhnologiya 10, no. 107 (2022): 13–19. http://dx.doi.org/10.36871/vet.zoo.bio.202210002.

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COVID-19 causes changes primarily in the respiratory system. Over time, more and more cases of COVID-19 have been reported in animals. It was relevant to classify the course of COVID-19 in dogs to predict outcome and plan therapy. The course of COVID-19 in dogs was divided by the authors into: mild, moderately severe, severe, extremely severe using complex diagnostics. Radiography made a significant contribution to determining the severity of the course of the pathological process. The more severe the clinical picture, the more intense was bronchial pattern dencity and interstitial changes lik

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Kanchan, Kumari, Kumari Asha, and Kumar Naveen. "A Study to Assess the Prescription Pattern to Promote Rational Use of Drugs: Cross-Sectional Descriptive Study." International Journal of Current Pharmaceutical Review and Research 16, no. 01 (2024): 296–99. https://doi.org/10.5281/zenodo.11543060.

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AbstractAim: The aim of the present study was to assess the prescription pattern to promote rational use of drugs.Methods: A cross-sectional descriptive study was done for one year in DMCH in Darbhanga. Prescriptions fromOut-patient departments especially Medicine and Pediatrics were collected and analyzed. The prescribed fixeddose combination drugs and other drugs were categorized according to Anatomical Therapeutic Chemicalclassification (ATC classification).Results: Most common FDCs in elderly age group belonged to Gastrointestinal system and in Pediatric populationmainly respiratory system

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Ansari, Mohammed Shahnawaz, Pradeep Singh, Raghav Awasthi, Tav Pritesh Sethi, and Varinder Singh. "Spectral pattern of cough sounds as an aid to diagnosis in children with common respiratory diseases." International Journal of Contemporary Pediatrics 12, no. 4 (2025): 632–36. https://doi.org/10.18203/2349-3291.ijcp20250770.

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Background: Objectives were to identify discriminatory spectral patterns of cough consistent with common respiratory sounds, through machine learning, to assist diagnosis. Methods: Spectral analysis of cough recordings of 50 children each with crackles alone, wheezing alone and absence of crackles and wheezing. Identification of unique features through machine learning by dividing them into training (75%) and testing (25%) datasets. Feature extraction was done using R python and Librosa programming language. Two class classifications of the features extracted from the training dataset were don

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Arizmendi, Carlos, Jhon Reinemer, Hernando Gonzalez, and Beatriz F. Giraldo. "Diagnosis of patients with chronic heart failure implementing wavelet transform and machine learning techniques." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 4 (2024): 4577. http://dx.doi.org/10.11591/ijece.v14i4.pp4577-4589.

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Chronic heart failure (CHF) is a significant public health concern due to its increasing prevalence, high number of hospital admissions, and associated mortality. Its prevalence is progressively increasing due to the aging of the population and the decrease in mortality from acute myocardial infarction, among other medical advancements. Consequently, the incidence of CHF predominantly affects older age groups, doubling its prevalence every decade, becoming one of the main causes of mortality in patients older than 65 years. The main objective of this study is to apply machine learning based te

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Hung, Jung-Jyh, Yi-Chen Yeh, Wen-Juei Jeng, et al. "Predictive Value of the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification of Lung Adenocarcinoma in Tumor Recurrence and Patient Survival." Journal of Clinical Oncology 32, no. 22 (2014): 2357–64. http://dx.doi.org/10.1200/jco.2013.50.1049.

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Purpose This study investigated the pattern of recurrence of lung adenocarcinoma and the predictive value of histologic classification in resected lung adenocarcinoma using the new International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification system. Patients and Methods Histologic classification of 573 patients undergoing resection for lung adenocarcinoma was determined according to the IASLC/ATS/ERS classification system, and the percentage of each histologic component (lepidic, acinar, papillary, micropapilla

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Stacey, RM, A. Vyas, and SJ Fowler. "P231 Breathing pattern disorders in a complex breathlessness service; classification and clinical characteristics." Thorax 71, Suppl 3 (2016): A212.1—A212. http://dx.doi.org/10.1136/thoraxjnl-2016-209333.374.

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Arizmendi, Carlos, Jhon Reinemer, Hernando Gonzalez, and Giraldo Beatriz F. "Diagnosis of patients with chronic heart failure implementing wavelet transform and machine learning techniques." Diagnosis of patients with chronic heart failure implementing wavelet transform and machine learning techniques 14, no. 4 (2024): 4577–89. https://doi.org/10.11591/ijece.v14i4.pp4577-4589.

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Chronic heart failure (CHF) is a significant public health concern due to its increasing prevalence, high number of hospital admissions, and associated mortality. Its prevalence is progressively increasing due to the aging of the population and the decrease in mortality from acute myocardial infarction, among other medical advancements. Consequently, the incidence of CHF predominantly affects older age groups, doubling its prevalence every decade, becoming one of the main causes of mortality in patients older than 65 years. The main objective of this study is

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Subramaniam, Umashankar, M. Monica Subashini, Dhafer Almakhles, Alagar Karthick, and S. Manoharan. "An Expert System for COVID-19 Infection Tracking in Lungs Using Image Processing and Deep Learning Techniques." BioMed Research International 2021 (November 13, 2021): 1–17. http://dx.doi.org/10.1155/2021/1896762.

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The proposed method introduces algorithms for the preprocessing of normal, COVID-19, and pneumonia X-ray lung images which promote the accuracy of classification when compared with raw (unprocessed) X-ray lung images. Preprocessing of an image improves the quality of an image increasing the intersection over union scores in segmentation of lungs from the X-ray images. The authors have implemented an efficient preprocessing and classification technique for respiratory disease detection. In this proposed method, the histogram of oriented gradients (HOG) algorithm, Haar transform (Haar), and loca

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Warth, Arne, Thomas Muley, Michael Meister, et al. "The Novel Histologic International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification System of Lung Adenocarcinoma Is a Stage-Independent Predictor of Survival." Journal of Clinical Oncology 30, no. 13 (2012): 1438–46. http://dx.doi.org/10.1200/jco.2011.37.2185.

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Purpose Our aim was to analyze and validate the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) proposal for an architectural classification of invasive pulmonary adenocarcinomas (ADCs) across all tumor stages. Patients and Methods The architectural pattern of a large cohort of 500 patients with resected ADCs (stages I to IV) was retrospectively analyzed in 5% increments and classified according to their predominant architecture (lepidic, acinar, solid, papillary, or micropapillary)

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Purnomo, Ariana Tulus, Ding-Bing Lin, Tjahjo Adiprabowo, and Willy Fitra Hendria. "Non-Contact Monitoring and Classification of Breathing Pattern for the Supervision of People Infected by COVID-19." Sensors 21, no. 9 (2021): 3172. http://dx.doi.org/10.3390/s21093172.

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During the pandemic of coronavirus disease-2019 (COVID-19), medical practitioners need non-contact devices to reduce the risk of spreading the virus. People with COVID-19 usually experience fever and have difficulty breathing. Unsupervised care to patients with respiratory problems will be the main reason for the rising death rate. Periodic linearly increasing frequency chirp, known as frequency-modulated continuous wave (FMCW), is one of the radar technologies with a low-power operation and high-resolution detection which can detect any tiny movement. In this study, we use FMCW to develop a n

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Raji, Rafiu King, Michael Adjeisah, Xuhong Miao, and Ailan Wan. "A novel respiration pattern biometric prediction system based on artificial neural network." Sensor Review 40, no. 1 (2020): 8–16. http://dx.doi.org/10.1108/sr-10-2019-0235.

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Purpose The purpose of this paper is to introduce a novel respiration pattern-based biometric prediction system (BPS) by using artificial neural network (ANN). Design/methodology/approach Respiration patterns were obtained using a knitted piezoresistive smart chest band. The ANN model was implemented by using four hidden layers to help achieve the best complexity to produce an adequate fit for the data. Not only did this study give a detailed distribution of an ANN model construction including the scheme of parameters and network layers, ablation of the architecture and the derivation of back-

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Kesuma, Lucky Indra, and Rudiansyah Rudiansyah. "Classification of Covid-19 Diseases Through Lung CT-Scan Image Using the ResNet-50 Architecture." Computer Engineering and Applications Journal 12, no. 1 (2023): 11–30. http://dx.doi.org/10.18495/comengapp.v12i1.425.

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Covid-19 is a respiratory tract disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The Covid-19 disease was first reported in Wuhan, China, in December 2019. The SARS-CoV-2 virus is primarily transmitted through human contact, and the World Health Organization has proclaimed a global pandemic (WHO). Symptoms of Covid-19 can range from asymptomatic to mild and severe. One way to diagnose Covid-19 disease can be done by examining lung abnormalities on the results of a Computed Tomography Scan (CT-Scan) of the lungs. However, determining the diagnostic results req

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Perez, I., C. Vadillo, M. A. Nieto, et al. "SAT0535 CLINICAL COURSE IN PATIENTS WITH INTERSTITIAL PNEUMONIA WITH AUTOIMMUNE FEATURES (IPAF) IN A MULTIDISCIPLINARY CONSULTATION." Annals of the Rheumatic Diseases 79, Suppl 1 (2020): 1225.1–1225. http://dx.doi.org/10.1136/annrheumdis-2020-eular.4607.

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Background:A proportion of patients with Interstitial Lung Disease (ILD) show autoimmune characteristics but do not completely meet the classification criteria for a definitive connective tissue disease. In order to unify the nomenclature and criteria to define this condition, the classification of patients with Interstitial Pneumonia with Autoimmune Features (IPAF) has recently been adopted (Fisher, et al).Objectives:To describe the sociodemographic, clinical, functional characteristics and therapeutic management of IPAF patients in clinical practice and to evaluate the incidence rate of func

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Sinha, Abhinav, Jitendriya Amrit Pritam, Hitesh Kumar Jain, Sidhartha Giri, Sanghamitra Pati, and Jaya Singh Kshatri. "Seasonal variations in respiratory morbidity in primary care and its correlation with the quality of air in urban Odisha, India." PLOS Global Public Health 4, no. 1 (2024): e0002313. http://dx.doi.org/10.1371/journal.pgph.0002313.

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Poor air quality, especially in urban regions among low-and middle-income countries such as India poses a significant healthcare challenge. Amongst urban areas, metropolitan cities garner the utmost importance for air quality related policies and studies with limited studies from tier II cities which are thought to be relatively immune to air pollution. Hence, we aimed to identify the most frequent respiratory morbidities and explore its correlation with exposure to ambient PM2.5 particles in Bhubaneswar (a tier II city in coastal India), Odisha. A chart review was carried out through data ext

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Bettermann, H., D. Amponsah, D. Cysarz, and P. van Leeuwen. "Musical rhythms in heart period dynamics: a cross-cultural and interdisciplinary approach to cardiac rhythms." American Journal of Physiology-Heart and Circulatory Physiology 277, no. 5 (1999): H1762—H1770. http://dx.doi.org/10.1152/ajpheart.1999.277.5.h1762.

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The purpose of this study was to expand classic heart period analysis methods by techniques from ethnomusicology that explicitly take complex musical rhythm principles into consideration. The methods used are based on the theory of African music, the theory of symbolic dynamics, and combinatorial theory. Heart period tachograms from 192 24-h electrocardiograms of 96 healthy subjects were transformed into binary symbol sequences that were interpretable as elementary rhythmic (percussive) patterns, the time lines in African music. Using a hierarchical rhythm pattern scheme closely related to the

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Vadillo, C., M. A. Nieto, O. Sanchez Pernaute, et al. "POS1427 CLINICAL COURSE IN PATIENTS WITH INTERSTITIAL PNEUMONIA WITH AUTOIMMUNE FEATURES (IPAF): REAL-LIFE DATA FROM A MULTICENTER ILD REGISTRY." Annals of the Rheumatic Diseases 81, Suppl 1 (2022): 1056.2–1057. http://dx.doi.org/10.1136/annrheumdis-2022-eular.2396.

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BackgroundSeveral patients with Interstitial Lung Disease show autoimmune characteristics but do not meet the classification criteria for a connective tissue disease. In order to define this condition, the classification of patients with interstitial pneumonia with autoimmune features (IPAF) has been adopted (Fischer’s criteria).ObjectivesTo describe the sociodemographic, clinical, functional characteristics and therapeutic management of IPAF in clinical practice and to evaluate the incidence rate of functional respiratory impairment.MethodsA longitudinal observational study was performed (NER

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Karkouli, Georgia, Konstantinos Douros, Dafni Moriki, et al. "Dysfunctional Breathing in Children: A Literature Review." Children 11, no. 5 (2024): 556. http://dx.doi.org/10.3390/children11050556.

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Dysfunctional breathing (DB) describes a respiratory condition that is mainly characterized by abnormal breathing patterns, affecting both children and adults, often leading to intermittent or chronic complaints and influencing physiological, psychological, and social aspects. Some symptoms include breathlessness; dizziness; palpitations; and anxiety, while its classification lies in breathing pattern disorders and upper airway involvement. Its prevalence among the pediatric population varies with a female overrepresentation, while the existence of comorbidities in DB, such as asthma, gastro-e

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Gift Eyareosowo Oden, Himmat Singh, Santosh Kumar Singh, Abhay Raizada, and Gaurav Gupta. "A current update on viral classification, diagnosis and available treatment of COVID-19." Asian Pacific Journal of Nursing and Health Sciences 4, no. 1 (2021): 1–4. http://dx.doi.org/10.46811/apjnh/4.1.1.

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In December of 2019, an outbreak of a disease began at Wuhan, China and would later be named the coronavirus disease2019 (covid-19) by the World Health Organization and further declared a global pandemic. Since the onset of this disease, the pattern of day to day activities had been disrupted in a bid to curb this menace to society. This paper work touches on basic viral classification, as well as structure of the severe acute respiratory syndrome coronavirus 2, the main causative agent of covid-19. This review work also sheds light on symptoms associated with this disease, mode of transmissio

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Wang, Liang, Xing Wang, Miao Huang, et al. "High-risk-pattern lung adenocarcinoma with epidermal growth factor receptor mutation is associated with distant metastasis risk and may benefit from adjuvant targeted therapy." Interactive CardioVascular and Thoracic Surgery 33, no. 3 (2021): 395–401. http://dx.doi.org/10.1093/icvts/ivab099.

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Abstract OBJECTIVES This study aimed to evaluate the value of the high-risk-pattern histology (micropapillary and solid components) for predicting distant metastasis in lung adenocarcinoma and to determine the survival benefit with adjuvant targeted therapy for resected non-small cell lung cancer with high-risk-pattern histology. METHODS Patients receiving surgery for non-small cell lung cancer were included in this retrospective study. Histological classification was performed according to 2015 World Health Organization classification. Tumours with micropapillary and solid components were def

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Lenshin, A. V., E. A. Ignat’eva, A. V. Il’in, and J. M. Perelman. "To the question of reforming the classification of thoracic sarcoidosis." Bulletin Physiology and Pathology of Respiration, no. 79 (April 2, 2021): 8–20. http://dx.doi.org/10.36604/1998-5029-2021-79-8-20.

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Since the beginning of the 50s of the last century, numerous classifications of sarcoidosis have been proposed, which to one degree or another satisfied specialists at certain stages of the development of medical technologies. Currently, sarcoidosis of the respiratory system is divided into five stages (from 0 to IV) based on the results of chest Xray examination. Active introduction into clinical practice of computed tomography and its more advanced version – lowdose multislice computed tomography (MSCT) – allows to carry out an effective diagnosis of sarcoidosis, including in outpatient prac

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Berner, Karina, Eugene Nizeyimana, Diribsa Tsegaye Bedada, and Quinette A. Louw. "Multimorbidity patterns and function among adults in low- and middle-income countries: a scoping review." BMJ Open 15, no. 1 (2025): e096522. https://doi.org/10.1136/bmjopen-2024-096522.

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ObjectivesTo map the scope of available evidence on relationships between multimorbidity patterns and functioning among adults in low- and middle-income countries (LMICs), and describe methods used.DesignScoping review guided by a five-step methodological framework and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines.Data sourcesPubMed/MEDLINE, Scopus, EBSCOhost (CINAHL) and Cochrane databases were searched from January 1976 to March 2023, plus reference lists of included studies.Eligibility criteria for selecting studiesPeer

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Walsh, Simon L. F., Jan De Backer, Helmut Prosch, et al. "Towards the adoption of quantitative computed tomography in the management of interstitial lung disease." European Respiratory Review 33, no. 171 (2024): 230055. http://dx.doi.org/10.1183/16000617.0055-2023.

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The shortcomings of qualitative visual assessment have led to the development of computer-based tools to characterise and quantify disease on high-resolution computed tomography (HRCT) in patients with interstitial lung diseases (ILDs). Quantitative CT (QCT) software enables quantification of patterns on HRCT with results that are objective, reproducible, sensitive to change and predictive of disease progression. Applications developed to provide a diagnosis or pattern classification are mainly based on artificial intelligence. Deep learning, which identifies patterns in high-dimensional data

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Ibrahim, Riyadh M. "Morbidity and Mortality Pattern of Neonates Admitted to Neonatal Care Unit.Central Teaching Pediatric Hospital Baghdad." AL-Kindy College Medical Journal 16, no. 1 (2020): 38–48. http://dx.doi.org/10.47723/kcmj.v16i1.188.

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Background; Neonatal period is a very vulnerable period of life due to many problems, In spite of advances in perinatal and neonatal care still, the mortality rate of neonate high especially in developing country The World Health Organization estimates that globally four million neonatal deaths per year, Developing countries account for around 99% of the neonatal mortality in the world, In Iraq. Neonatal mortality rate about 19 per 1000 live births which represent 56% of child death below 5 years age in 2012. .Objectives The aims of the study were to determine the institutional new-born case f

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Gonem, Sherif, Wim Janssens, Nilakash Das, and Marko Topalovic. "Applications of artificial intelligence and machine learning in respiratory medicine." Thorax 75, no. 8 (2020): 695–701. http://dx.doi.org/10.1136/thoraxjnl-2020-214556.

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The past 5 years have seen an explosion of interest in the use of artificial intelligence (AI) and machine learning techniques in medicine. This has been driven by the development of deep neural networks (DNNs)—complex networks residing in silico but loosely modelled on the human brain—that can process complex input data such as a chest radiograph image and output a classification such as ‘normal’ or ‘abnormal’. DNNs are ‘trained’ using large banks of images or other input data that have been assigned the correct labels. DNNs have shown the potential to equal or even surpass the accuracy of hu

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Williams, E., Ricardo Colasanti, Kasope Wolffs, Paul Thomas, and Ben Hope-Gill. "Classification of Tidal Breathing Airflow Profiles Using Statistical Hierarchal Cluster Analysis in Idiopathic Pulmonary Fibrosis." Medical Sciences 6, no. 3 (2018): 75. http://dx.doi.org/10.3390/medsci6030075.

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In idiopathic pulmonary fibrosis (IPF) breathing pattern changes with disease progress. This study aims to determine if unsupervised hierarchal cluster analysis (HCA) can be used to define airflow profile differences in people with and without IPF. This was tested using 31 patients with IPF and 17 matched healthy controls, all of whom had their lung function assessed using spirometry and carbon monoxide CO transfer. A resting tidal breathing (RTB) trace of two minutes duration was collected at the same time. A Euclidian distance technique was used to perform HCA on the airflow data. Four disti

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Travis, William D., Elisabeth Brambilla, and Gregory J. Riely. "New Pathologic Classification of Lung Cancer: Relevance for Clinical Practice and Clinical Trials." Journal of Clinical Oncology 31, no. 8 (2013): 992–1001. http://dx.doi.org/10.1200/jco.2012.46.9270.

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We summarize significant changes in pathologic classification of lung cancer resulting from the 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) lung adenocarcinoma classification. The classification was developed by an international core panel of experts representing IASLC, ATS, and ERS with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. Because 70% of patients with lung cancer present with advanced stages, a new approach to small biopsies and cytology with s

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Andaç Baltacıoğlu, Nurten. "Latent class analysis for exploring distribution patterns of primary superficial venous insufficiency." Turkish Journal of Thoracic and Cardiovascular Surgery 28, no. 3 (2020): 474–79. http://dx.doi.org/10.5606/tgkdc.dergisi.2020.19144.

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Background: This study aims to identify specific segmental distribution patterns of lower extremity chronic venous disease based on latent class analysis of Doppler mapping results. Methods: A total of 1,871 lower extremities of 1,218 treatment-naïve patients (536 males, 682 females; mean age 45.4 years; range, 21 to 87 years) with chronic venous disease referred for Doppler examination between September 2009 and August 2018 were included. Refluxing superficial venous segments of the lower extremities were mapped and recorded in database in 10 distinct anatomic locations as follows: saphenofem

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El bouisfi, Radouane, Lamiaa El Menzhi, and Xavier Chiementin. "Supervised Classification Of induction Motors faults." E3S Web of Conferences 336 (2022): 00051. http://dx.doi.org/10.1051/e3sconf/202233600051.

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Currently, the environmental challenges have been considered as a strategic issue for most industrial companies around the world, threatening their sustainability and profit; This leads to taking the environmental dimensions seriously and preserving natural resources well, since they are a key criterion for sustainable development. In this context, this work calls for innovative solution and new technologies to support the development and integration of environmental considerations through the implementation of an automated fault detection and diagnosis system in induction machines in order to

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Sambataro, Gianluca, Domenico Sambataro, Sebastiano Emanuele Torrisi, et al. "State of the art in interstitial pneumonia with autoimmune features: a systematic review on retrospective studies and suggestions for further advances." European Respiratory Review 27, no. 148 (2018): 170139. http://dx.doi.org/10.1183/16000617.0139-2017.

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The term interstitial pneumonia with autoimmune features (IPAF) has been proposed to define patients with interstitial lung disease (ILD) associated with autoimmune signs not classifiable for connective tissue diseases (CTDs). This new definition overcomes previous nomenclatures and provides a uniform structure for prospective studies through specific classification criteria.This work evaluates the characteristics of IPAF patients reported in the literature, to highlight potential limits through a comparative analysis and to suggest better performing classification criteria.Four retrospective

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Bortoluzzi, Eduarda M., Paige H. Schmidt, Rachel E. Brown, et al. "Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle." Veterinary Sciences 10, no. 2 (2023): 113. http://dx.doi.org/10.3390/vetsci10020113.

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Bovine respiratory disease (BRD) and acute interstitial pneumonia (AIP) are the main reported respiratory syndromes (RSs) causing significant morbidity and mortality in feedlot cattle. Recently, bronchopneumonia with an interstitial pattern (BIP) was described as a concerning emerging feedlot lung disease. Necropsies are imperative to assist lung disease diagnosis and pinpoint feedlot management sectors that require improvement. However, necropsies can be logistically challenging due to location and veterinarians’ time constraints. Technology advances allow image collection for veterinarians’

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Lucà, Stefano, Francesca Pagliuca, Fabio Perrotta, et al. "Multidisciplinary Approach to the Diagnosis of Idiopathic Interstitial Pneumonias: Focus on the Pathologist’s Key Role." International Journal of Molecular Sciences 25, no. 7 (2024): 3618. http://dx.doi.org/10.3390/ijms25073618.

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Idiopathic Interstitial Pneumonias (IIPs) are a heterogeneous group of the broader category of Interstitial Lung Diseases (ILDs), pathologically characterized by the distortion of lung parenchyma by interstitial inflammation and/or fibrosis. The American Thoracic Society (ATS)/European Respiratory Society (ERS) international multidisciplinary consensus classification of the IIPs was published in 2002 and then updated in 2013, with the authors emphasizing the need for a multidisciplinary approach to the diagnosis of IIPs. The histological evaluation of IIPs is challenging, and different types o

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Mulyono, Tri, Asnawati Siswoyo, Puji Bunga Lestari, Zulfikar, and Yeni Maulidah Mufliha. "Development of A Resistive Sensor Array Based on Graphene and Conducting Polymer Composites for Coffee Aroma Classification." E3S Web of Conferences 481 (2024): 06012. http://dx.doi.org/10.1051/e3sconf/202448106012.

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This work aims to create a resistive sensor array for categorizing coffee from various plantations. A mixture of graphene oxide and a conductive polymer is used to create the sensor array. Eight types of sensors were made by dripping various mixtures of graphene oxide, polypyrrole, polyaniline, and poly acetate materials on the interdigitated electrode. Coffee fragrance gas was used for the sensor array test. The surface of the sensor array receives the scent gas created by the brewing of coffee grinds. Each sensor’s response profile is recorded. Each coffee sample has a distinct sensor respon

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Novak, Peter. "Cerebral Blood Flow, Heart Rate, and Blood Pressure Patterns during the Tilt Test in Common Orthostatic Syndromes." Neuroscience Journal 2016 (July 12, 2016): 1–20. http://dx.doi.org/10.1155/2016/6127340.

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Objective. The head-up tilt test is widely used for evaluation of orthostatic intolerance. Although orthostatic symptoms usually reflect cerebral hypoperfusion, the cerebral blood flow velocity (CBFv) profile in orthostatic syndromes is not well described. This study evaluated CBFv and cardiovascular patterns associated with the tilt test in common orthostatic syndromes. Methods. This retrospective study analyzed the tilt test of patients with history of orthostatic intolerance. The following signals were recorded: ECG, blood pressure, CBFv using transcranial Doppler, respiratory signals, and

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Zhang, Jiaosheng, Wenshuang Zhang, Xiang Ma, et al. "Antimicrobial prescribing for children in China: data from point prevalence surveys in 18 tertiary centres in China in 2016–2017." BMJ Open 12, no. 9 (2022): e059244. http://dx.doi.org/10.1136/bmjopen-2021-059244.

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ObjectivesThe reports on evaluating the classification of antibiotic agents prescribed for Chinese children by combining WHO’s and China’s administrative categories were rare. This study aimed to investigate the pattern of antimicrobial agents prescribing for Chinese children in 2016.Settings18 tertiary centres from nine provinces located in northern, southern, eastern and western China.ParticipantsThe antimicrobial prescribing data from the children admitted in medical wards, surgical wards and intensive care units were collected and analysed. A total of 3680 antibiotic prescriptions for Chin

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Jyoshna, R., B. Jyothi, P. Sandhya, et al. "Early Classification of Emphysema in CT Scans Using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 1194–200. http://dx.doi.org/10.22214/ijraset.2024.63296.

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Abstract: Learning about Lung Diseases and their characterization is one of the most interesting research topics in recent years. With the various uses of medical images in hospitals, pathologies, and diagnostic centers, the size of the medical image datasets is also expanding expeditiously to capture the diseases in hospitals. Though a lot of research has been done on this particular topic still this field is confusing and challenging. There are lots of techniques in literature to classify medical images. The main drawback of traditional methods is the semantic gap that exists between the low

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